Timeseer offers an AI‑driven industrial data validation platform that detects anomalies, validates sensor data fitness, and provides root‑cause analysis for millions of IIoT devices. The solution automates data cleaning, correction, and audit‑ready reporting, enabling reliable inputs for analytics, digital twins, billing, and regulatory compliance.
Funding
$6M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
3OFounders
Product
Problem
Industrial operations rely on massive streams of sensor data, but drifted, flatlined, or missing readings introduce “data downtime” that erodes trust, leads to inaccurate billing, regulatory non‑compliance, and sub‑optimal decision making.
Solution
Timeseer provides an AI‑driven industrial data validation platform that detects anomalies, validates data fitness, and resolves issues across millions of IIoT devices. The system automatically flags spikes, drifts, flatlines and other artefacts using over 100 built‑in checks and machine‑learning models that learn from each customer’s data. Detected incidents are grouped and enriched with root‑cause analysis, enabling teams to clean data manually, apply automated correction, or trigger sensor maintenance. Validated, fit‑for‑purpose data can then be streamed to downstream analytics, digital twins, billing systems, or regulatory reporting pipelines via APIs, SDKs, or out‑of‑the‑box integrations. The platform supports on‑prem, cloud, or SaaS deployments and includes auditability, role‑based access, and single sign‑on for enterprise governance.
Target Audience
Primary customers are industrial data engineers, digital twin teams, and operations managers in utilities, process manufacturing, energy trading, and regulated sectors that need reliable sensor data for analytics, billing, and compliance.
Features
- AI‑powered anomaly detection covering flatlines, spikes, drifts, and missing values across any sensor type
- Over 100 industry‑specific validation checks and ready‑made templates for utilities, manufacturing, energy trading, and more
- Incident grouping and root‑cause analysis workflow that turns raw alerts into actionable insights
- Manual and fully automated data cleaning, with configurable cleaning algorithms and triage actions
- Seamless integration via REST APIs, Python SDK, GitOps support, and pre‑built connectors for OT/IT systems
- Full audit trail, traceability, and role‑based permissions to meet compliance and governance requirements
- Flexible deployment options: on‑premises, private cloud, or managed SaaS with SSO support